Standing on the shoulders of a giant: The legacy of Robert M. Sellers.

Robert M. Sellers, PhD, most known for his influential and highly cited Multidimensional Model of Racial Identity (MMRI), is one of the most prolific and foundational Black scholars in psychology. From racial identity theory development and measurement to conceptual and methodological innovations in studying the lived experiences of Black people, Sellers' scholarship centers on the lives of Black communities. Sellers' mentorship and contributions to the professional development of scholars and professionals of color have supported and catalyzed new intergenerational knowledge building by these scholars, ensuring a perpetuating and far-reaching legacy in psychology. In this article, we: (a) celebrate Sellers' enduring contribution to the racial identity literature and its profound impact on psychology as a discipline as well as numerous subfields of psychology, (b) outline his contributions to the racial socialization literature, (c) describe methodological innovations in racial identity and racial socialization research advanced through his scholarship, and (d) summarize his contributions in professional development and mentorship and his leadership roles. Sellers' scholarly contributions and mentorship have transformed the discipline of psychology and the social sciences broadly speaking, making him one of the most influential psychologists in the modern era. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Teaching transformation: Fostering critical awareness through transformative justice organizing frameworks.

The following article explores how the curricular adaptation of seminal and contemporary definitions of and approaches to transformative justice frameworks can foster student's critical reflection from identity awareness toward critical action informed by collectivist perspectives of social change. Applications in the social work curriculum are presented.

Supratherapeutic Tacrolimus Concentrations With Nirmatrelvir/Ritonavir in Solid Organ Transplant Recipients Requiring Hospitalization: A Case Series Using Rifampin for Reversal.

Nirmatrelvir/ritonavir was recently granted emergency use authorization for mild to moderate coronavirus disease 2019. Drug-drug interactions between ritonavir and tacrolimus are underappreciated by nontransplant providers. We describe 2 solid organ transplant recipients prescribed nirmatrelvir/ritonavir for outpatient use who developed tacrolimus toxicity requiring hospitalization and were managed with rifampin for toxicity reversal.

Efficacy of Inhaled Essential Oil Use on Selected Symptoms Affecting Quality of Life in Patients With Cancer Receiving Infusion Therapies.

OBJECTIVES: To evaluate the effects of inhaled ginger, German chamomile, and bergamot essential oil (EO) versus an odorless control oil on appetite, anxiety, fatigue, and nausea in individuals with cancer receiving IV therapy. SAMPLE & SETTING: 248 adults with gastrointestinal, neuroendocrine, or skin cancer receiving IV therapy from an academic cancer center. RETHODS & VARIABLES: Participants were randomized to EO or control oil groups. Participants rated their symptoms during a seven-day period using a Likert-type scale ranging from 0 (no symptoms) to 10 (worst symptoms ever). RESULTS: Symptom burden was low. More men than women completed the study. The majority of participants had gastrointestinal cancer, followed by skin and neuroendocrine cancer. Ginger EO produced statistically significant results for anxiety and fatigue. IMPLICATIONS FOR NURSING: Most participants were men and had gastrointestinal cancer. The high number of zero scores for symptoms may indicate the success of current symptom management regimens. Improvements in anxiety and fatigue using ginger EO warrant further study for validation.

Signal and measurement considerations for human translation of diffuse in vivo flow cytometry.

SIGNIFICANCE: "Diffuse in vivo flow cytometry" (DiFC) is an emerging technology for fluorescence detection of rare circulating cells directly in large deep-seated blood vessels in mice. Because DiFC uses highly scattered light, in principle, it could be translated to human use. However, an open question is whether fluorescent signals from single cells would be detectable in human-scale anatomies. AIM: Suitable blood vessels in a human wrist or forearm are at a depth of ∼2 to 4 mm. The aim of this work was to study the impact of DiFC instrument geometry and wavelength on the detected DiFC signal and on the maximum depth of detection of a moving cell. APPROACH: We used Monte Carlo simulations to compute fluorescence Jacobian (sensitivity) matrices for a range of source and detector separations (SDS) and tissue optical properties over the visible and near infrared spectrum. We performed experimental measurements with three available versions of DiFC (488, 640, and 780 nm), fluorescent microspheres, and tissue mimicking optical flow phantoms. We used both computational and experimental data to estimate the maximum depth of detection at each combination of settings. RESULTS: For the DiFC detection problem, our analysis showed that for deep-seated blood vessels, the maximum sensitivity was obtained with NIR light (780 nm) and 3-mm SDS. CONCLUSIONS: These results suggest that-in combination with a suitable molecularly targeted fluorescent probes-circulating cells and nanosensors could, in principle, be detectable in circulation in humans.

Long-term adherence of human brain cells in vitro is enhanced by charged amine-based plasma polymer coatings.

Advances in cellular reprogramming have radically increased the use of patient-derived cells for neurological research in vitro. However, adherence of human neurons on tissue cultureware is unreliable over the extended periods required for electrophysiological maturation. Adherence issues are particularly prominent for transferable glass coverslips, hindering imaging and electrophysiological assays. Here, we assessed thin-film plasma polymer treatments, polymeric factors, and extracellular matrix coatings for extending the adherence of human neuronal cultures on glass. We find that positive-charged, amine-based plasma polymers improve the adherence of a range of human brain cells. Diaminopropane (DAP) treatment with laminin-based coating optimally supports long-term maturation of fundamental ion channel properties and synaptic activity of human neurons. As proof of concept, we demonstrated that DAP-treated glass is ideal for live imaging, patch-clamping, and optogenetics. A DAP-treated glass surface reduces the technical variability of human neuronal models and enhances electrophysiological maturation, allowing more reliable discoveries of treatments for neurological and psychiatric disorders.

White Parents' Socialization of Racial Attitudes: A Commentary on Scott et al. (2020).

In the September 2020 issue of Perspectives, Scott et al. argued that there is insufficient empirical work on White parents' racial-socialization strategies to support generalizations about the topic and, therefore, that journalists' recommendation that White parents discuss race and racism with their children represents a case of speculation without evidence. Although we strongly support Scott et al.'s call for additional, rigorous research on racial socialization in White families, we argue that their critique of popular-press pieces was unwarranted. Specifically, we argue that, although definitive tests of the effects of specific White parental racial-socialization strategies are lacking, the recommendation for parents to discuss race and racism with their children is both appropriate and empirically grounded. We describe research on racial socialization, intergroup contact, and cognitive development that is consistent with recommendations from developmental scientists reported in the popular press. Furthermore, we argue that parents may be the ideal socializers of racial attitudes. We conclude with a discussion of the broad context concerning media reports of findings from psychological science.

Predicting Posttraumatic Stress Disorder Among Survivors of Recent Interpersonal Violence.

A substantial minority of women who experience interpersonal violence will develop posttraumatic stress disorder (PTSD). One critical challenge for preventing PTSD is predicting whose acute posttraumatic stress symptoms will worsen to a clinically significant degree. This 6-month longitudinal study adopted multilevel modeling and exploratory machine learning (ML) methods to predict PTSD onset in 58 young women, ages 18 to 30, who experienced an incident of physical and/or sexual assault in the three months prior to baseline assessment. Women completed baseline assessments of theory-driven cognitive and neurobiological predictors and interview-based measures of PTSD diagnostic status and symptom severity at 1-, 3-, and 6-month follow-ups. Higher levels of self-blame, generalized anxiety disorder severity, childhood trauma exposure, and impairment across multiple domains were associated with a pattern of high and stable posttraumatic stress symptom severity over time. Predictive performance for PTSD onset was similarly strong for a gradient boosting machine learning model including all predictors and a logistic regression model including only baseline posttraumatic stress symptom severity. The present findings provide directions for future work on PTSD prediction among interpersonal violence survivors that could enhance early risk detection and potentially inform targeted prevention programs.

Assessing consistency among indices to measure socioeconomic barriers to health care access.

Many places within rural America lack ready access to health care facilities. Barriers to access can be both spatial and non-spatial. Measurements of spatial access, such as the Enhanced Floating 2-Step Catchment Area and other floating catchment area measures, produce similar patterns of access. However, the extent to which different measurements of socioeconomic barriers to access correspond with each other has not been examined. Using West Virginia as a case study, we compute indices based upon the literature and measure the correlations among them. We find that all indices positively correlate with each other, although the strength of the correlation varies. Also, while there is broad agreement in the general spatial trends, such as fewer barriers in urban areas, and more barriers in the impoverished southwestern portion of the state, there are regions within the state that have more disagreement among the indices. These indices are to be used to support decision-making with respect to placement of rural residency students from medical schools within West Virginia to provide students with educational experiences as well as address health care inequalities within the state. The results indicate that for decisions and policies that address statewide trends, the choice of metric is not critical. However, when the decisions involve specific locations for receiving rural residents or opening clinics, the results can become more sensitive to the selection of the index. Therefore, for fine-grained policy decision-making, it is important that the chosen index best represents the processes under consideration.

Symptoms of Depression, Anxiety, Post-Traumatic Stress Disorder, and Suicidal Ideation Among State, Tribal, Local, and Territorial Public Health Workers During the COVID-19 Pandemic - United States, March-April 2021.

Increases in mental health conditions have been documented among the general population and health care workers since the start of the COVID-19 pandemic (1-3). Public health workers might be at similar risk for negative mental health consequences because of the prolonged demand for responding to the pandemic and for implementing an unprecedented vaccination campaign. The extent of mental health conditions among public health workers during the COVID-19 pandemic, however, is uncertain. A 2014 survey estimated that there were nearly 250,000 state and local public health workers in the United States (4). To evaluate mental health conditions among these workers, a nonprobability-based online survey was conducted during March 29-April 16, 2021, to assess symptoms of depression, anxiety, post-traumatic stress disorder (PTSD), and suicidal ideation among public health workers in state, tribal, local, and territorial public health departments. Among 26,174 respondents, 52.8% reported symptoms of at least one mental health condition in the preceding 2 weeks, including depression (30.8%), anxiety (30.3%), PTSD (36.8%), or suicidal ideation (8.4%). The highest prevalence of symptoms of a mental health condition was among respondents aged ≤29 years (range = 13.6%-47.4%) and transgender or nonbinary persons (i.e., those who identified as neither male nor female) of all ages (range = 30.4%-65.5%). Public health workers who reported being unable to take time off from work were more likely to report adverse mental health symptoms. Severity of symptoms increased with increasing weekly work hours and percentage of work time dedicated to COVID-19 response activities. Implementing prevention and control practices that eliminate, reduce, and manage factors that cause or contribute to public health workers' poor mental health might improve mental health outcomes during emergencies.

Smartphone Time Machine: Tech-Supported Improvements in Time Perspective and Wellbeing Measures.

Individuals with a balanced time perspective, which includes good thoughts about the past, awareness of present constraints and adaptive planning for a positive future, are more likely to report optimal wellbeing. However, people who have had traumas such as adverse childhood experiences (ACEs) are likely to have less balanced time perspectives and lower overall wellbeing when compared to those with fewer or no ACEs. Time perspective can be improved via time-travel narratives that support people in feeling connected to a wise and loving future version of themselves, an approach that has until now only been provided in counseling contexts. Our team used an iterative inclusive design process to shape a scalable time-travel narrative tool - a responsive and progressive web application called Time Machine. Among other functionalities, Time Machine allowed people to record and listen to messages as if they were from and to their past and future selves. Using pre-planned as well as post-hoc analyses, we analyzed quantitative and qualitative data from 96 paid design partners (participants) who were taken through a 26-day pilot study of the technology. Among other effects, the results revealed: (1) high engagement throughout the design process, (2) improvements in self-reported time perspective and overall wellbeing scores that were greater for those using Time Machine during an optional-use period, (3) twice as much improvement in overall wellbeing scores for design partners with high ACEs (16%) versus low ACEs (8%), and (4) feelings of unconditional love apparently mediating the relationship between scores on time perspective and overall wellbeing measures. We discuss the limitations of these results as well as implications for the future role of spiritually informed scalable time-travel narrative technologies in healthcare and wellness.

Predicting pain among female survivors of recent interpersonal violence: A proof-of-concept machine-learning approach.

Interpersonal violence (IPV) is highly prevalent in the United States and is a major public health problem. The emergence and/or worsening of chronic pain are known sequelae of IPV; however, not all those who experience IPV develop chronic pain. To mitigate its development, it is critical to identify the factors that are associated with increased risk of pain after IPV. This proof-of-concept study used machine-learning strategies to predict pain severity and interference in 47 young women, ages 18 to 30, who experienced an incident of IPV (i.e., physical and/or sexual assault) within three months of their baseline assessment. Young women are more likely than men to experience IPV and to subsequently develop posttraumatic stress disorder (PTSD) and chronic pain. Women completed a comprehensive assessment of theory-driven cognitive and neurobiological predictors of pain severity and pain-related interference (e.g., pain, coping, disability, psychiatric diagnosis/symptoms, PTSD/trauma, executive function, neuroendocrine, and physiological stress response). Gradient boosting machine models were used to predict symptoms of pain severity and pain-related interference across time (Baseline, 1-,3-,6- follow-up assessments). Models showed excellent predictive performance for pain severity and adequate predictive performance for pain-related interference. This proof-of-concept study suggests that machine-learning approaches are a useful tool for identifying predictors of pain development in survivors of recent IPV. Baseline measures of pain, family life impairment, neuropsychological function, and trauma history were of greatest importance in predicting pain and pain-related interference across a 6-month follow-up period. Present findings support the use of machine-learning techniques in larger studies of post-IPV pain development and highlight theory-driven predictors that could inform the development of targeted early intervention programs. However, these results should be replicated in a larger dataset with lower levels of missing data.

Symptoms of Depression, Anxiety, Post-Traumatic Stress Disorder, and Suicidal Ideation Among State, Tribal, Local, and Territorial Public Health Workers During the COVID-19 Pandemic - United States, March-April 2021.

Increases in mental health conditions have been documented among the general population and health care workers since the start of the COVID-19 pandemic (1-3). Public health workers might be at similar risk for negative mental health consequences because of the prolonged demand for responding to the pandemic and for implementing an unprecedented vaccination campaign. The extent of mental health conditions among public health workers during the COVID-19 pandemic, however, is uncertain. A 2014 survey estimated that there were nearly 250,000 state and local public health workers in the United States (4). To evaluate mental health conditions among these workers, a nonprobability-based online survey was conducted during March 29-April 16, 2021, to assess symptoms of depression, anxiety, post-traumatic stress disorder (PTSD), and suicidal ideation among public health workers in state, tribal, local, and territorial public health departments. Among 26,174 respondents, 53.0% reported symptoms of at least one mental health condition in the preceding 2 weeks, including depression (32.0%), anxiety (30.3%), PTSD (36.8%), or suicidal ideation (8.4%). The highest prevalence of symptoms of a mental health condition was among respondents aged ≤29 years (range = 13.6%-47.4%) and transgender or nonbinary persons (i.e., those who identified as neither male nor female) of all ages (range = 30.4%-65.5%). Public health workers who reported being unable to take time off from work were more likely to report adverse mental health symptoms. Severity of symptoms increased with increasing weekly work hours and percentage of work time dedicated to COVID-19 response activities. Implementing prevention and control practices that eliminate, reduce, and manage factors that cause or contribute to public health workers' poor mental health might improve mental health outcomes during emergencies.

Use of remdesivir in the presence of elevated LFTs for the treatment of severe COVID-19 infection.

An 82-year-old man with an extensive medical history presented to the emergency room with complaints of generalised weakness and cough. He tested positive for COVID-19 10 days prior to presenting to the emergency room. Although his symptoms started a week prior to diagnosis, his weakness increased, warranting emergency response. A comprehensive metabolic panel was drawn from the patient on admission, indicating markedly high liver function tests (LFTs) ≥20 times above the upper limit of normal. On day 1 of admission, the decision was still made to start remdesivir (5-day course) due to decompensated acute respiratory failure as well as dexamethasone. The patient's LFTs significantly improved throughout his hospital stay. The patient made a full recovery and was discharged on day 10 of hospitalisation.

Short-Term Circulating Tumor Cell Dynamics in Mouse Xenograft Models and Implications for Liquid Biopsy.

MOTIVATION: Circulating tumor cells (CTCs) are widely studied using liquid biopsy methods that analyze fractionally-small peripheral blood (PB) samples. However, little is known about natural fluctuations in CTC numbers that may occur over short timescales in vivo, and how these may affect detection and enumeration of rare CTCs from small blood samples. METHODS: We recently developed an optical instrument called "diffuse in vivo flow cytometry" (DiFC) that uniquely allows continuous, non-invasive counting of rare, green fluorescent protein expressing CTCs in large blood vessels in mice. Here, we used DiFC to study short-term changes in CTC numbers in multiple myeloma and Lewis lung carcinoma xenograft models. We analyzed CTC detections in over 100 h of DiFC data, and considered intervals corresponding to approximately 1%, 5%, 10%, and 20% of the PB volume. In addition, we analyzed changes in CTC numbers over 24 h (diurnal) periods. RESULTS: For rare CTCs (fewer than 1 CTC per ml of blood), the use of short DiFC intervals (corresponding to small PB samples) frequently resulted in no detections. For more abundant CTCs, CTC numbers frequently varied by an order of magnitude or more over the time-scales considered. This variance in CTC detections far exceeded that expected by Poisson statistics or by instrument variability. Rather, the data were consistent with significant changes in mean numbers of CTCs on the timescales of minutes and hours. CONCLUSIONS: The observed temporal changes can be explained by known properties of CTCs, namely, the continuous shedding of CTCs from tumors and the short half-life of CTCs in blood. It follows that the number of cells in a blood sample are strongly impacted by the timing of the draw. The issue is likely to be compounded for multicellular CTC clusters or specific CTC subtypes, which are even more rare than single CTCs. However, we show that enumeration can in principle be improved by averaging multiple samples, analysis of larger volumes, or development of methods for enumeration of CTCs directly in vivo.

Dynamics and determinants of cortisol and alpha-amylase responses to repeated stressors in recent interpersonal trauma survivors.

BACKGROUND: Alterations in major stress response systems are present during the immediate aftermath of trauma and may play a role in determining risk for developing posttraumatic stress disorder (PTSD). However, the dynamics and determinants of stress responses during this acute recovery phase, and their relevance for longitudinal clinical course and prognosis, have yet to be fully examined. The objectives of the present study were to characterize stress response and habituation patterns to repeated social stressors in women who recently experienced interpersonal trauma and to determine the extent to which these stress responses were associated with PTSD during prospective follow-up. METHOD: This longitudinal study examined salivary cortisol and alpha-amylase and heart rate (HR) responses to repeated stressors in 98 young women (ages 18-30). Participants included women who had experienced an incident of interpersonal trauma (i.e., physical and/or sexual assault) in the three months prior to their baseline assessment (n = 58) and a comparison group of healthy, non-traumatized women (n = 40). Women completed the Trier Social Stress Test (TSST), clinical interviews to evaluate posttraumatic stress symptom severity at the baseline assessment and again at 1-, 3-, and 6-month follow-ups. RESULTS: Multilevel models revealed a pattern of robust initial cortisol TSST responses and habituation across successive TSSTs; alpha-amylase and HR responses showed no evidence of habituation across TSSTs. Among interpersonal trauma survivors, current PTSD status was associated with more pronounced cortisol responses to the first TSST. Survivors exhibited similarly blunted cortisol responses across follow-up TSSTs regardless of PTSD status, suggesting habituation of cortisol responses among survivors who developed PTSD. PTSD re-experiencing symptoms were uniquely associated with blunting of cortisol TSST responses. CONCLUSION: Findings suggest that PTSD as a diagnostic entity is meaningfully associated with cortisol responses to repeated social stressors. Social-evaluative threat is a salient form of danger for interpersonal trauma survivors. Identifying the determinants of cortisol (non)habituation to repeated social-evaluative threat among interpersonal trauma survivors could inform the development of early interventions for PTSD.

Identifying Cardiac Diseases using Cardiac Biomarkers in Rhesus Macaques (Macaca mulatta).

Cardiac biomarkers are an important tool for diagnosing cardiac diseases in both human and veterinary patients. Serum concentrations of N-terminal probrain natriuretic peptide (NT-proBNP) and cardiac troponin I (cTnI) have been used to indicate the presence of various cardiac diseases including hypertrophic cardiomyopathy (HCM) in various species including humans. However, these cardiac biomarkers have not been established as a diagnostic tool for detecting cardiac disease in rhesus macaques. In the rhesus macaque colony at the California National Primate Research Center, naturally occurring HCM and various other cardiac diseases have been identified. In this study, commercially available assays were used to measure serum cTnI and NT-proBNP concentrations to evaluate their utility as a diagnostic screening tool for cardiac diseases in rhesus macaques. This study revealed that the serum cTnI concentration was significantly higher in animals with echocardiographically apparent cardiac disease as compared with the animals that had no cardiac structural and functional changes (the control group). However, no significant differences were detected between animals with HCM and non-HCM cardiac disease. Because the area under the receiver operating characteristic curve was 0.81 when the serum cTnI was compared between the control and cardiac disease groups, serum cTnI was considered a moderately accurate test to predict the presence of cardiac disease. The optimal cut-off value of serum cTnI concentration for diagnosis of cardiac disease was 0.0085 ng/mL, with a sensitivity of 0.68 and specificity of 0.94. Significant but weak correlations were noted between the serum cTnI concentration and several echocardiographic parameters. Conversely, no significant differences in NT-proBNP concentrations were detected between animals with and without cardiac diseases. In conclusion, measurement of serum cTnI can be used to aid in diagnosing cardiac diseases in rhesus macaques. However, cTnI measurement does not replace echocardiographic evaluation to diagnose cardiac diseases in rhesus macaques due to the poor sensitivity of the assay and the weak correlation to with more established echocardiographic markers for cardiac disease.

Correlations Between the USMLE Step Examinations, American College of Physicians In-Training Examination, and ABIM Internal Medicine Certification Examination.

PURPOSE: To assess the correlations between United States Medical Licensing Examination (USMLE) performance, American College of Physicians Internal Medicine In-Training Examination (IM-ITE) performance, American Board of Internal Medicine Internal Medicine Certification Exam (IM-CE) performance, and other medical knowledge and demographic variables. METHOD: The study included 9,676 postgraduate year (PGY)-1, 11,424 PGY-2, and 10,239 PGY-3 internal medicine (IM) residents from any Accreditation Council for Graduate Medical Education-accredited IM residency program who took the IM-ITE (2014 or 2015) and the IM-CE (2015-2018). USMLE scores, IM-ITE percent correct scores, and IM-CE scores were analyzed using multiple linear regression, and IM-CE pass/fail status was analyzed using multiple logistic regression, controlling for USMLE Step 1, Step 2 Clinical Knowledge, and Step 3 scores; averaged medical knowledge milestones; age at IM-ITE; gender; and medical school location (United States or Canada vs international). RESULTS: All variables were significant predictors of passing the IM-CE with IM-ITE scores having the strongest association and USMLE Step scores being the next strongest predictors. Prediction curves for the probability of passing the IM-CE based solely on IM-ITE score for each PGY show that residents must score higher on the IM-ITE with each subsequent administration to maintain the same estimated probability of passing the IM-CE. CONCLUSIONS: The findings from this study should support residents and program directors in their efforts to more precisely identify and evaluate knowledge gaps for both personal learning and program improvement. While no individual USMLE Step score was as strongly predictive of IM-CE score as IM-ITE score, the combined relative contribution of all 3 USMLE Step scores was of a magnitude similar to that of IM-ITE score.